Senior Database, Data Warehouse Consultant

Jobtailor; Dublin; On-site; EUR 120,000 - 160,000; Full time

Job summary

Jobtailor in Ireland is seeking a senior data integration lead to architect and deliver enterprise-scale data integration solutions using Microsoft Fabric, Azure Data Factory and related technologies. You will design scalable pipelines, enforce data quality and governance, and mentor internal teams across hybrid cloud and on‑prem environments.

Responsibilities include leading data integration projects, building robust ETL/ELT solutions, and optimizing performance and reliability across diverse

Qualifications

• 7+ years experience in data integration, data engineering, or data warehouse consultancy.
• Experience delivering enterprise-scale data integration solutions.
• Strong experience with Microsoft Fabric, Azure Data Factory, and related tools.
• Experience with hybrid cloud and on-premises platforms.
• Deep SQL and data engineering skills.
• Experience implementing monitoring, logging, and exception handling frameworks.

Responsibilities

• Lead the design and implementation of enterprise data integration solutions.
• Develop scalable Microsoft Fabric Data Factory and Azure Data Factory pipelines.
• Design and support enterprise integration frameworks and standards.
• Implement robust ETL/ELT solutions across cloud and on-premises environments.
• Build data ingestion, transformation, orchestration, and monitoring capabilities.
• Design and implement data quality frameworks, validation controls, reconciliation processes, logging and alerting mechanisms.
• Support batch and near real-time data integration patterns.
• Optimize integration performance, scalability, and reliability.
• Document architecture, interfaces, pipelines, and data flows.
• Provide technical mentorship and knowledge transfer to internal teams.

Skills

Data integration

Data engineering

SQL proficiency

Data governance

Education

Degree in Computer Science or related field

Tools

Microsoft Fabric

Fabric Data Factory

Azure Data Factory

Azure SQL

SQL Server

Lakehouse architectures

Job description

Responsibilities

• Lead the design and implementation of enterprise data integration solutions.
• Develop scalable Microsoft Fabric Data Factory and Azure Data Factory pipelines.
• Design and support enterprise integration frameworks and standards.
• Implement robust ETL/ELT solutions across cloud and on-premises environments.
• Build data ingestion, transformation, orchestration, and monitoring capabilities.
• Design and implement:
  • Data quality frameworks
  • Validation controls
  • Reconciliation processes
  • Logging and alerting mechanisms
• Support batch and near real-time data integration patterns.
• Optimize integration performance, scalability, and reliability.
• Document architecture, interfaces, pipelines, and data flows.
• Provide technical mentorship and knowledge transfer to internal teams.

Requirements

• 7+ years' experience in data integration, data engineering, or data warehouse consultancy.
• Proven experience delivering enterprise-scale data integration solutions.
• Strong experience with:
  • Microsoft Fabric
  • Fabric Data Factory
  • Azure Data Factory
  • Azure SQL
  • SQL Server
  • Lakehouse and Warehouse architectures
• Extensive ETL/ELT design and implementation experience.
• Experience integrating hybrid cloud and on-premises platforms.
• Strong SQL and data engineering skills.
• Experience implementing monitoring, logging, and exception-handling frameworks.
• Deep understanding of data quality, governance, and integration best practices.

Preferred Qualifications

• Degree in Computer Science, Data Engineering, Information Technology, or related field.
• Microsoft Azure Data Engineer certification or equivalent.
• Microsoft Fabric certification.

Core Competencies

Demonstrates expertise in designing and implementing enterprise data integration solutions, with a strong focus on Microsoft Fabric, Azure Data Factory, and ETL/ELT processes. Proven ability to optimize data integration performance and ensure data quality and governance across hybrid cloud and on-premises environments.